Identification of the Binary Choice Model with Misclassification
Misclassification in binary choice (binomial response) models occurs when the dependent variable is measured with error, that is, when an actual "one" response is sometimes recorded as a zero, and vice versa. This paper shows that binary choice models with misclassification are semiparametrically identified, even when the probabilities of misclassification depend in unknown ways on model covariates, and the distribution of the errors is unknown.
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